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App para detetar e separar maçãs em pequenas, grandes ou defeituosas. / App to detect and sort apples in small, big or defective.

Batchfile 0.08% Python 98.74% C++ 1.18%
app apples categorization computervision fruits numpy opencv pyqt6 python qualitycontrol

projeto1_esan-ua_2023-2024's Introduction

Apple Quality Control Application

Overview

This application is designed for quality control of apples, utilizing detection and subsequent sorting based on size and condition (Large/Small/Defective). It detects apples either by color or alternatively by object detection using a YOLO model trained with the COCO dataset. It further classifies apples as defective using a pre-trained KERAS model with a dataset of both rotten and good apples.

Technologies Used

  • Python 3.10
  • OpenCV
  • Keras
  • PyQt6
  • Pyserial

Dependencies

  • Numpy
  • opencv-python
  • keras
  • pyqt6
  • configmanager
  • pyserial

Usage

  1. Install Python from Python Official Website.

  2. Install the required dependencies using the following command:

pip install numpy opencv-python keras pyqt6 configmanager pyserial
  1. Download the SourceCode and put the models.zip content (downloaded from the releases) inside the modules folder.

  2. Run the application using the command or use the executable version from the releases:

python main.py
  1. Follow the on-screen instructions to input apples for quality control, and view the results.

  2. Alternatively, you can use the precompiled executable version of the application available in the AppleCategorizationApp_EXE.zip.


Aplicação de Controlo de Qualidade de Maçãs

Visão Geral

Esta aplicação é projetada para o controle de qualidade de maçãs, utilizando a detecção e subsequente classificação com base no tamanho e estado (Grande/Pequena/Defeituosa). Ela detecta maçãs pela cor ou, alternativamente, pela detecção de objetos usando um modelo YOLO treinado com o conjunto de dados COCO. Além disso, classifica as maçãs como defeituosas usando um modelo KERAS pré-treinado com um conjunto de dados de maçãs podres e boas.

Tecnologias Utilizadas

  • Python 3.10
  • OpenCV
  • Keras
  • PyQt6
  • Pyserial

Dependências

  • Numpy
  • opencv-python
  • keras
  • pyqt6
  • configmanager
  • pyserial

Utilização

  1. Instale o Python a partir do site oficial do Python.

  2. Instale as dependências necessárias usando o seguinte comando:

pip install numpy opencv-python keras pyqt6 configmanager pyserial
  1. Faça download do sourcecode e do models.zip (disponível nas releases) e coloque o conteúdo na pasta modules.

  2. Execute a aplicação com o comando ou abra a versão executável disponível nas releases:

python main.py
  1. Siga as instruções na tela para inserir maçãs para controle de qualidade e visualize os resultados.

  2. Alternativamente, você pode usar a versão executável pré-compilada do aplicativo disponível no arquivo AppleCategorizationApp_EXE.zip.

projeto1_esan-ua_2023-2024's People

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